1. Field of the Invention
The invention relates to a spatial filter measuring arrangement that comprises a sensor and a spatial filter, wherein electromagnetic radiation, in particular, light that is emitted or reflected from a measure object is imaged by the spatial filter onto the sensor. The invention further relates to a spatial filter measuring device, the use of a mirror array as a spatial filter in a spatial filter measuring arrangement, and to a method for effecting spatial filter measurement.
2. Description of Related Art
The measuring technology of spatial filters is a well-established, robust, and efficient method for effecting noncontact measurement of the velocities of measuring objects, such as, for example, gases, fluids, or solid bodies. The measuring technology of spatial filters functions free of wear and reliably without any mechanical moving parts. There is no slippage nor physical wear to degrade the measurement or the apparatus. In addition to velocity measurement, accelerations, the location or position of measuring objects, or other application-specific parameters can also be measured, such as volumetric flow rate or material flow, particle sizes or particle size distributions.
A major portion of the signal processing that is associated with converting motion into a (spatial) frequency has already been implemented in the constructive design of known spatial filter measuring devices or spatial filter measuring arrangements since these constitute a hardware correlator. An excellent point source is not required in order to effect a spatial filter measurement. Image information is correlated and a motion-equivalent frequency is generated. The signal analysis provides a simple and strong reduction of data.
In simplified terms, spatial filter measuring technology is based on the principle that a moving object or a moving surface generates a periodic signal when moving past an optical grating having a, possibly periodic, structure of transparent and nontransparent grating lines, the frequency of this signal being a function both of the velocity of the object's motion, as well as of the grating parameters or grating constants of the optical grating. Incorporated in this dependent relationship are also, for example, magnification factors from optical lenses, lens systems, or other optical elements that are employed in some cases.
If the grating structure is known, and it is optionally also known what magnification factor the optical means has that is used within the optical path of a spatial filter measuring arrangement, it is possible to us the frequency of the observed signal to infer the velocity of motion for the measuring object. In the case, for example, of a linear grating with parallel grating lines, what is measured here is the velocity component of the motion that is perpendicular to the orientation of the grating lines. A velocity component that is parallel to the orientation of the grating lines does not produce any modulation of the light passing through the grating. This component is therefore not measured.
In the case of a uniform motion, a linear grating used as a spatial filter yields a frequency response with a pronounced maximum that corresponds to the motion component of the measuring object perpendicular to the orientation of the grating lines. Another frequency spectrum is optionally superimposed on this frequency maximum, which spectrum arises due to any surface roughness present on the surface of the measuring object. The spatial frequencies generated by the regularities or irregularities of the surface can be utilized as the measuring effect; however, they can also result in uncertainties or ambiguities in the interpretation of the measurement results.
There are essentially two known approaches to effecting spatial filter measurement. In a first approach, the spatial filter measurement is implemented using hardware spatial filters. These spatial filters involve discrete construction elements, such as optical gratings. The light that passes from a moving measuring object is thereby modulated over time. The modulation frequency depends, among other things, on the velocity of the measuring object and on the orientation of the optical grating, and on its grating parameter or grating constant. If magnification optics are used, the modulation frequency also increases along with the magnification factor.
The time-modulated light is detected, for example, by photodiodes that have a high cutoff frequency, such as, for example, 10 MHz or up into the GHz range. In this first approach, the fast reaction time of photodiodes enables very fast signals and very high frequencies to be processed in the spatial filter measurement—as long as sufficient light is available. To this end, the hardware, thus optionally the optics used and the spatial filters used, are adapted to the given conditions of use—for example, in terms of the velocities to the measured, of the surface properties of the measuring objects. What the adaptation achieves is to adjust the optimum modulation signals for the given conditions of use and the parameters to be measured. This is intended to avoid uncertainties or destructive resonances, for example, with the grating parameters of the spatial filter and to achieve an effective signal-to-noise ratio.
This first approach using discrete optical construction elements as the spatial grating provides very high time resolution for the measurement enabled by the possibility of using very fast receivers. Adaptation of the hardware is, however, costly. Low flexibility means that it is possible that uncertainties in the measurement results and unwanted correlations on surface parameters will sometimes not be recognized.
The second approach eliminates the need for using hardware spatial filters. Instead, spatial filter measurement is implemented by special signal processing of line-type or two-dimensional receivers, e.g., cameras using CCD or CMOS chips. In this case, no optical gratings are required; instead, the grating-like or matrix-like structuring of the optical receiver is exploited to effect the spatial filter measurement.
Spatial filter measurement here comprises producing the correlation or summation of signals from individual pixels, where computational means are used to generate a spatial filter effect. Thus different spatial filters can be applied without modifying the hardware solely based on a software-adjustable modification of the used evaluation routines. This is analogous to exchanging optical gratings based on the above-referenced approach. Spatial filter measurement using the second approach is very flexible and can be easily adapted to various conditions of use. Complex spatial filter algorithms and correction algorithms can be implemented, thereby enabling any possible uncertainties and errors to be significantly minimized.
However, the limiting speed of CCD and CMOS chips is smaller by several orders of magnitude than for photodiodes. For CCDs or CMOS sensors, this speed is approximately 10 kHz to 20 kHz. These sensors, however, do not allow for continuous measurement since the volume of image data cannot be not transmitted and processed in real-time. Due to the slow signal response of these sensors, the time resolution of the measurement is significantly more limited than with the first approach. As a result, only a fraction of the bandwidth of the spatial filter spectrum can be achieved as compared with the first approach, with the result that the second approach is cannot be used in those cases where high spatial frequencies predominate. Due to this lower time resolution, it is not possible in all cases of application to eliminate the uncertainties in the measurement signal and reach an unambiguous measurement result.
In light of these known approaches to effecting spatial filter measurement, the object of the invention is to provide a spatial filter measurement, a spatial filter measuring device, and a method for effecting spatial filter measurement that enable a reliable, precise and uncertainties-preventing spatial filter measurement to be achieved, which furthermore should be able to be flexibly adapted to different areas of application.